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Observational analysis reveals local environmental regionalization best classifies phytoplankton, suggesting multi-scale approaches optimize freshwater biomonitoring.
Several studies have tested whether biological communities correspond to regionalizations derived from large-scale environmental drivers (e.g., ecoregions). However, few studies have focused on testing the correspondence of communities to regionalizations based on local environmental factors. Here, we compared the ability of regionalizations based on ecoregions and local environmental variables to discriminate spatial patterns of phytoplankton, zooplankton, and macroinvertebrate communities. We used data from 979 U.S. lakes sampled by the National Lake Assessment Program to test the hypothesis that plankton communities – due to their low dispersal limitation – would respond primarily to regionalizations based on local environmental variables, whereas macroinvertebrate communities would be better predicted by ecoregional delineations. Both environmental regionalizations (ecoregions or environmental clusters) discriminated planktonic and macroinvertebrate compositions better than chance. Phytoplankton communities were better represented by the regionalization based on local environmental variables than by the ecoregions, while zooplankton and macroinvertebrates were similarly represented by the regionalizations based on local environmental variables and ecoregions. Thus, our results partially supported the initial hypothesis. Our findings highlight the importance of integrating multiple spatial scales in biodiversity assessments and biomonitoring programs, thereby improving ecological inference and informing conservation strategies in freshwater ecosystems.
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Liborio et al. (2025) studied this question.
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